Triple

T15763234
Position Surface form Disambiguated ID Type / Status
Subject Novosibirsk State Technical University E382149 entity
Predicate alsoKnownAs P39 FINISHED
Object NETI
NETI is the commonly used abbreviation for Novosibirsk State Technical University, a major technical higher education institution in Novosibirsk, Russia.
 E1176061 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: NETI | Statement: [Novosibirsk State Technical University, alsoKnownAs, NETI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: NETI
Context triple: [Novosibirsk State Technical University, alsoKnownAs, NETI]
  • A. Nete
    The Nete is a river in Belgium that flows through the Flemish region and serves as one of the main tributaries forming the Rupel River.
  • B. Netolicky
    Netolicky is the surname of Bob Netolicky, an American former professional basketball player known for his career in the American Basketball Association (ABA).
  • C. Netishyn
    Netishyn is a small city in western Ukraine known primarily for hosting the Khmelnytskyi Nuclear Power Plant.
  • D. Netia
    Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
  • E. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: NETI
Triple: [Novosibirsk State Technical University, alsoKnownAs, NETI]
Generated description
NETI is the commonly used abbreviation for Novosibirsk State Technical University, a major technical higher education institution in Novosibirsk, Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: NETI
Target entity description: NETI is the commonly used abbreviation for Novosibirsk State Technical University, a major technical higher education institution in Novosibirsk, Russia.
  • A. Nete
    The Nete is a river in Belgium that flows through the Flemish region and serves as one of the main tributaries forming the Rupel River.
  • B. Netolicky
    Netolicky is the surname of Bob Netolicky, an American former professional basketball player known for his career in the American Basketball Association (ABA).
  • C. Netishyn
    Netishyn is a small city in western Ukraine known primarily for hosting the Khmelnytskyi Nuclear Power Plant.
  • D. Netia
    Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
  • E. Netze
    Netze is the German name for the Noteć, a river in north-central Poland that is a tributary of the Warta.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d86da09a10819082fe9797b23e4664 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b6c9fc8190a1bcf763c4b04b12 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8776c2488190ad27fd79e2ce4e14 completed May 9, 2026, 7:13 p.m.
NEDg Description generation batch_69ff8b6c44d081908e35ca17b5ce2189 completed May 9, 2026, 7:30 p.m.
NED2 Entity disambiguation (via description) batch_69ff8ca1c1f08190aeb6f7421d54c2de completed May 9, 2026, 7:36 p.m.
Created at: April 10, 2026, 4:47 a.m.